Department of Global Business, Yeungnam University, Gyeongsan, Korea.
Department of Physical Education, Yeungnam University, Gyeongsan, Korea.
PLoS One. 2024 Oct 24;19(10):e0309784. doi: 10.1371/journal.pone.0309784. eCollection 2024.
Intelligent manufacturing enterprises play a crucial role in the modern industrial system and are key to high-quality economic development. However, most current research on intelligent manufacturing technology innovation focuses on single variables, lacking a comprehensive analysis from a linkage grouping perspective. This paper constructs an analytical framework for the technology innovation path of intelligent manufacturing enterprises from three dimensions: technology level, organization level, and environment level. Six antecedent variables are selected: R&D investment, digital transformation, human capital structure, profitability, government support, and competitive position. Using the fuzzy sets of qualitative comparative analysis (fsQCA) methodology, the paper examines the technological innovation paths of intelligent manufacturing enterprises in China. The research indicates that no single antecedent variable is necessary for high technological innovation; instead, the innovation path results from the synergistic effect of multiple conditions. The study identifies three paths leading to high technological innovation in intelligent manufacturing:"Government and Human Resource driven types," "Environmental-Organizational linkage types,"and"Organizational Resilience dominant types." This analysis provides reference suggestions for enterprises to adopt suitable development strategies based on their competitive positions.
智能制造企业在现代工业体系中扮演着至关重要的角色,是实现高质量经济发展的关键。然而,当前大多数关于智能制造技术创新的研究都集中在单一变量上,缺乏从关联分组角度的综合分析。本文从技术水平、组织水平和环境水平三个维度构建了智能制造企业技术创新路径的分析框架。选择了六个前置变量:研发投入、数字化转型、人力资本结构、盈利能力、政府支持和竞争地位。利用模糊集定性比较分析(fsQCA)方法,考察了中国智能制造企业的技术创新路径。研究表明,没有单一的前置变量是实现高技术创新的必要条件,而是多个条件的协同作用导致了创新路径。研究发现了三种通往智能制造高技术创新的路径:“政府和人力资源驱动型”、“环境-组织关联型”和“组织弹性主导型”。该分析为企业根据竞争地位采取合适的发展战略提供了参考建议。